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Neuraxio / Neuraxle

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
https://www.neuraxle.org/
Apache License 2.0
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Feature: Integration with sklearn-evaluation #531

Open idomic opened 1 year ago

idomic commented 1 year ago

Is your feature request related to a problem? Please describe. I think adding an integration/tutorial and the right documentation of the framework can go a long way.

Here's a sample flow

User calls Neuraxle and fit function with training data. It would then generate the plots for model assessment and performance evaluation (based on user's the predictions).

Describe the solution you'd like Usually, when using Neuraxle you'd get the final model, and then you'll check performance and results. This will allow an easier mechanism for the users to solve the second part of it.

Describe alternatives you've considered Currently users have to get their own custom package and write extra code to achieve it.

stale[bot] commented 3 months ago

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs in the next 180 days. Thank you for your contributions.